cursorrules

.cursorrules

@project-documentation(projectName: "open-deep-research - Ultimate Development Guide & Code Snippets Collection") {

@section(name: "Project Overview", level: 1) { @project-overview { @short-description: "open-deep-research: Your AI-Powered Research Assistant. Conduct iterative, deep research using search engines, web scraping, and Gemini LLMs, all within a lightweight and understandable codebase." @mcp-tool-availability: "Seamlessly Integrate with AI Agents via MCP. Available as a Model Context Protocol (MCP) tool for easy integration into larger AI agent systems." @core-libraries: "Powered by Key Libraries. Leverages Firecrawl for efficient web data extraction and Gemini for advanced language understanding and report generation." @goal: "Keep it Simple, Keep it Deep. Provides the simplest yet most effective implementation of a deep research agent, designed for clarity and easy extension (<500 LoC goal). " @workflow-reference: "Workflow Diagram Included. Refer to the 'Project Workflow Diagram' section for a visual representation of the research process." @license: "MIT Licensed. Freely use, modify, and build upon open-deep-research under the permissive MIT License." } @note: "Key Project Philosophy: 'open-deep-research' prioritizes simplicity and clarity, aiming to provide a foundational research agent that is easy to understand, modify, and extend. It's designed to be a starting point for building more sophisticated AI-driven research tools." }

@section(name: "Project Workflow Diagram", level: 1) { @workflow-diagram(description: "Mermaid flowchart representation of the Deep Research workflow (see README)") { @flowchart-mermaid { ```mermaid flowchart TB subgraph Input Q[User Query] B[Breadth Parameter] D[Depth Parameter] end

        DR[Deep Research] -->
        SQ[SERP Queries] -->
        PR[Process Results]

        subgraph Results[Results]
            direction TB
            NL((Learnings))
            ND((Directions))
        end

        PR --> NL
        PR --> ND

        DP{depth > 0?}

        RD["Next Direction:
        - Prior Goals
        - New Questions
        - Learnings"]

        MR[Markdown Report]

        %% Main Flow
        Q & B & D --> DR

        %% Results to Decision
        NL & ND --> DP

        %% Circular Flow
        DP -->|Yes| RD
        RD -->|New Context| DR

        %% Final Output
        DP -->|No| MR

        %% Styling
        classDef input fill:#7bed9f,stroke:#2ed573,color:black
        classDef process fill:#70a1ff,stroke:#1e90ff,color:black
        classDef recursive fill:#ffa502,stroke:#ff7f50,color:black
        classDef output fill:#ff4757,stroke:#ff6b81,color:black
        classDef results fill:#a8e6cf,stroke:#3b7a57,color:black

        class Q,B,D input
        class DR,SQ,PR process
        class DP,RD recursive
        class MR output
        class NL,ND results
    ```
  }
  @note: "**Workflow Visualization:** This Mermaid diagram provides a visual overview of the core research process within 'open-deep-research'.  Use it to understand the flow of data and control within the agent."
}

}

@section(name: "Key Features", level: 1) { @features-section(description: "Key features of the open-deep-research agent") { @feature(name: "MCP Integration", description: "MCP Ready: Seamlessly integrates as a Model Context Protocol tool into AI agent ecosystems, enabling plug-and-play research capabilities.") @feature(name: "Iterative Research", description: "Iterative Deep Dive: Explores topics deeply through iterative query refinement and result processing, mimicking the in-depth approach of expert human researchers.") @feature(name: "Intelligent Query Generation", description: "Gemini-Powered Queries: Leverages the power of Gemini LLMs to generate smart, targeted search queries, adapting to research goals and accumulated learnings for optimal information retrieval.") @feature(name: "Depth & Breadth Control", description: "Tuneable Research Scope: Offers highly configurable depth and breadth parameters, allowing users to precisely control the scope and intensity of research exploration, from focused investigations to broad surveys.") @feature(name: "Smart Follow-up Questions", description: "Clarify Research Needs with Follow-up Questions: Intelligently generates follow-up questions to refine ambiguous user queries, ensuring the research agent is precisely aligned with the user's intended topic.") @feature(name: "Comprehensive Markdown Reports", description: "Detailed, Ready-to-Use Markdown Reports: Generates well-structured, human-readable Markdown reports, summarizing key findings, insights, and providing a clear list of sources for verification and further exploration.") @feature(name: "Concurrent Processing for Speed", description: "Efficient & Fast with Concurrent Processing: Maximizes research efficiency and speed by handling multiple searches and data analysis tasks in parallel, leveraging asynchronous operations.") } @note: "Feature Highlights: These key features are designed to make 'open-deep-research' a powerful, versatile, and efficient research tool, while maintaining a clear and understandable codebase." }